diff --git a/research/cv/SE-Net/export.py b/research/cv/SE-Net/export.py index 5453b9ed4b489857aebc40dddd8ba431376d3eb3..57ffe5aa87ed839f749ec46ba195e904c098e061 100644 --- a/research/cv/SE-Net/export.py +++ b/research/cv/SE-Net/export.py @@ -28,7 +28,7 @@ if config.device_target == "Ascend": def run_export(): """run export.""" if config.network_dataset == 'se-resnet50_imagenet2012': - from src.resnet import resnet50 as resnet + from src.resnet import se_resnet50 as resnet elif config.network_dataset == 'se-resnet101_imagenet2012': from src.resnet import resnet101 as resnet else: diff --git a/research/cv/u2net/export.py b/research/cv/u2net/export.py index 1b3bb1a1cca18371fab02b4118833293630cdfdb..e48d13b752e60280a587e528ee86a0d2b70134e6 100644 --- a/research/cv/u2net/export.py +++ b/research/cv/u2net/export.py @@ -31,7 +31,6 @@ args = parser.parse_args() context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target) if __name__ == '__main__': - context.set_context(device_id="Ascend") net = U2NET() param_dict = load_checkpoint(args.ckpt_file) load_param_into_net(net, param_dict) diff --git a/research/cv/vit_base/src/modeling_ms.py b/research/cv/vit_base/src/modeling_ms.py index dba23f9fc37342ba282e74f89c4911b988362218..a81a5b434c232d1800996bfbe982354b5881447c 100644 --- a/research/cv/vit_base/src/modeling_ms.py +++ b/research/cv/vit_base/src/modeling_ms.py @@ -27,9 +27,6 @@ def swish(x): return x * P.Sigmoid()(x) -ACT2FN = {"gelu": nn.GELU(), "relu": P.ReLU(), "swish": swish} - - class Attention(nn.Cell): """Attention""" def __init__(self, config): @@ -87,7 +84,7 @@ class Mlp(nn.Cell): weight_init='XavierUniform', bias_init='Normal') self.fc2 = nn.Dense(config.transformer_mlp_dim, config.hidden_size, weight_init='XavierUniform', bias_init='Normal') - self.act_fn = ACT2FN["gelu"] + self.act_fn = nn.GELU() self.dropout = nn.Dropout(config.transformer_dropout_rate) def construct(self, x): diff --git a/research/cv/yolov3_tiny/scripts/run_standalone_train.sh b/research/cv/yolov3_tiny/scripts/run_standalone_train.sh index 7285ac714978b23a466ea628ddf7f8e6a45c7630..29adf4b1e9ece4cffdccaea59a118c1b64067e5c 100644 --- a/research/cv/yolov3_tiny/scripts/run_standalone_train.sh +++ b/research/cv/yolov3_tiny/scripts/run_standalone_train.sh @@ -50,7 +50,9 @@ then fi mkdir ./train cp ../*.py ./train +cp ../*.yaml ./train cp -r ../src ./train +cp -r ../model_utils ./train cd ./train || exit echo "start training for device $DEVICE_ID" env > env.log @@ -66,4 +68,4 @@ python train.py \ --per_batch_size=32 \ --weight_decay=0.016 \ --lr_scheduler=cosine_annealing > log.txt 2>&1 & -cd .. \ No newline at end of file +cd ..